Evolutionary biology and ecology (DARWIN)

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

General properties viewed through regression and one-factor ANOVA (R2, F, ddl, least squares, likelihood, diagnosis, validation, goodness of fit, interpretation of effect sizes); nested and crossed factor ANOVA, multiple regression (concept of parameters and effects, and interaction)

incorporation of the dependence of explanatory random variables, confounding effects (quantitative for multiple regression, and unbalanced designs for ANOVAs)

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The overall objective is to consolidate the foundations in ecology acquired by students and to give them the tools they need to apply them in an integrated way to interpret the functioning of ecological systems. The course includes: 1) lectures on ecological concepts from the population scale to the macroecological scale, using examples of applications that place the discipline in the current ecological and societal context; 2) practical and supervised work focused on tools (sampling strategies, modeling, data analysis); 3) field teaching, during which students are encouraged to ask relevant scientific questions based on their observations in the field and to use their knowledge to answer them in a reasoned manner.

Summary of EU content:

- 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;

- Field: Integrative analysis of ecosystem functioning in situ;

- TD/TP: sampling and experimentation strategies in ecology; modeling in population dynamics/metapopulations, community ecology/metacommunities, food webs; biodiversity measures (alpha, beta, etc.).

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The overall objective is to consolidate students' foundations in 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 to provide a solid foundation of knowledge in evolutionary biology and to illustrate the applications of the discipline to students' future areas of specialization. The course includes: 1) lectures on the concepts of evolution; 2) practical work in two main forms: 2a. sessions focused on the use of tools (phylogeny) and the mathematical formalization of evolutionary processes (population genetics); and 2b: sessions built around group work, allowing students, depending on their background and professional goals, to explore a particular topic in depth (fundamental question or application of evolutionary biology).

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English tutorial courses aimed at developing professional autonomy in the English language.

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The phylogenetic tree is a central concept in biology for students studying "Biodiversity, Ecology & Evolution," "Agricultural Biology," and "Eco-epidemiology." To address phylogeny, this course is divided into two successive parts, each lasting 22.5 hours: "Phylogeny and Evolution (Basics)" (HAB708B) and "Phylogeny and Evolution (Advanced)" (HAB714B).

The following subjects will be taught:

(i) History of the concept of evolution [Basics].

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

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

(iv) Phylogenetic inference methods 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 (bootstrap, topology comparison, multigenic corroboration, gene and species trees) [Advanced].

(viii) Applications to the phylogeny of some major taxonomic groups (mammals, eukaryotes) [Advanced].

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Generalized linear mixed models + methodology and experimental protocols to account for biological reality: non-normal distribution and pseudo-replication

Protocol optimization, power, and uncontrolled type I risk: variable transformation, polynomial regression, link function, likelihood, model selection

Deviance and goodness-of-fit analysis

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

Graphical representation of predictions.

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The objective of this course unit is to provide the necessary statistical foundations for following the more advanced modules in the curriculum; it is therefore a general refresher course. Descriptive statistics are reviewed (quantiles, cumulative frequency polygons, sample estimators), simple tests are presented, essential graphs for univariate and multivariate data are presented, and the general principle of a statistical test, hypothesis testing, the concept of p-value, and Type I and Type II errors are presented. In practical work, students are also brought up to speed in the R environment.

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The phylogenetic tree is a central concept in biology for students studying "Biodiversity, Ecology & Evolution," "Agricultural Biology," and "Eco-epidemiology." To address phylogeny, this course is divided into two successive parts, each lasting 22.5 hours: "Phylogeny and Evolution (Basics)" (HAB708B) and "Phylogeny and Evolution (Advanced)" (HAB714B).

The following subjects will be taught:

(i) History of the concept of evolution [Basics].

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

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

(iv) Phylogenetic inference methods 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 (bootstrap, topology comparison, multigenic corroboration, gene and species trees) [Advanced].

(viii) Applications to the phylogeny of some major taxonomic groups (mammals, eukaryotes) [Advanced].

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This EU has three objectives:

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

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

3) Finally, the EU is proposing a bioanalysis project using an empirical dataset to understand evolutionary genomics analysis and tackle the increasingly sophisticated bioinformatics aspects of the discipline.

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The individual M1 internship lasts approximately three months and, depending on the program, must be completed in a research laboratory or a non-academic organization. It allows students to gain professional experience in the field of biodiversity, evolution, or ecology. It can be carried out in a local, national, or international organization, on a topic approved by the teaching team so as to fit in with the objectives specific to the program followed by the student.

Assessment: Preparation for the internship is assessed on the basis of a written document and a presentation of the internship project. The internship work is assessed during a public presentation before a panel, during which the content of the dissertation and the quality of the responses to the panel's questions are evaluated. The student's behavior and enthusiasm during the internship are assessed by the internship supervisor.

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The objective of this course is to consolidate students' foundations in ecology and/or evolution by inviting them to define a research topic and question(s), formulate relevant hypotheses with supporting arguments, and justify a data acquisition and analysis strategy for testing them.

Summary of EU content:

- Independent work under supervision: identification of a relevant scientific question; bibliographic review to establish the state of the art and justify scientific hypotheses; proposal and justification of a methodological approach (materials and methods) to test the proposed hypotheses.

Types of topics:

Topics may cover any issue identified by students (in groups of 3/4) and approved by the teaching team, and may be based on different approaches to suit the requirements of different courses. For example, students may propose a field sampling or experimentation strategy, a meta-analysis of literature data, an analysis of sequences retrieved from GenBank, an analysis of occurrence data retrieved from GBIF, etc.

In all cases, projects must involve a genuine data acquisition strategy, identified, justified, and described by students in the materials and methods required for M1S2, with a provisional schedule for the project and identification of the tasks that each student will carry out within each group as part of the implementation of the project in M2S3. Projects must also be financially realistic and include a provisional budget, and must be able to be completed within the time available in M2S3.

Assessment methods:

Teaching is based on a problem-based learning approach. Students are assessed on how they progress in developing their approach (40% of the final grade), as well as on their ability to present and defend their project in a final oral exam (60% of the final grade).

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This module presents table management and the link between multivariate and univariate analysis: matrix manipulation and common operations; the concepts of projection and distance; translation of descriptive and univariate statistics using multiple regression/ACP/AFD as examples; indices of (dis)similarity, distance; correlation.

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"The objective of this course is to complement the teachings of the first semester by developing issues related to the evolution of phenotypes and the main methodological approaches associated with them. The teachings will address the evolution of different types of traits (life history traits, traits involved in reproductive strategies, traits involved in biotic interactions, quantitative traits). The main approaches covered include the formalization of game theory, adaptive dynamics, quantitative genetics approaches, 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 studies 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, we will study the role of spatial and temporal 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 the past and present diversity of organisms. We will also address the impact of human activities and global changes on biodiversity on a planetary scale.

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- First, give students a foundation of computer knowledge and skills, providing them with a solid basis for learning and using bioinformatics tools used more specifically in evolution and ecology.

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

- Thirdly, have students work on concrete examples that they can reuse during their master's internship and in their future professional life.

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The Darwin Field School runs for one week with the following objectives:

- Create group dynamics and integration in the promotion of the DARWIN-BEE Master 2 program.

- Analyze ecological issues in their technical, scientific, and social dimensions (e.g., reintroduction operations).

- Addressing biodiversity management issues in a humanized protected area.

- Present your findings orally and discuss them with the group; course review.

Activities in Florac:

- Discover the landscapes of the Causse Méjean.

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

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

- Conduct individual work in three subgroups on different scientific and ethical topics.

Activities around Montpellier:

- Study bird migration and ecosystems along the Mediterranean coast.

- Practicing urban ecology.

- Discover the wildlife of the Mediterranean scrubland, with daytime hikes along the Buèges river (discovering the insect fauna) and evening hikes (bat and/or moth and nocturnal orthopteran watching).

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The module covers the following fundamental topics in evolutionary biology: Microevolution, Macroevolution, Fitness, Natural and Sexual Selection, Speciation. Other topics (mutation, epigenetics, evo-devo, etc.) are presented by the students themselves.

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The objective of this EU is to support students in developing their career plans and searching for internships, while beginning to prepare for their integration into professional life by providing a comprehensive and personalized overview of possible career paths.

In practical terms, meetings with various stakeholders provide an opportunity to present the doctoral thesis (presentation of the GAIA doctoral school, presentations by doctoral students) and the professional network targeted by the various courses (research professions and non-academic sector). Activities specific to each course then enable students to better target the scientific fields most relevant to their professional projects. Finally, tutorial sessions are designed to prepare students for writing scientific articles in English.

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The objective of this course 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 in these major ecological themes is presented by specialists in these fields. This overview is followed by one or more examples illustrating the conceptual basis for formulating a relevant and novel research question and how to answer it using different methodologies, particularly experimental ones, drawn from the researchers' own work. After choosing one of these major themes, each student develops an original research project (the size of an M2 internship), conducting bibliographic research and proposing a coherent experimental plan to test hypotheses. This project is presented to the speakers and other students.

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1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

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The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

See the full page

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

See the full page

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

See the full page

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

See the full page

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

See the full page

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

See the full page

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

See the full page

The module addresses theoretical and empirical advances in recent research in evolutionary genetics through a number of key issues:

- Theme 1: Genetic burden and evolution of reproductive systems: recombination, sexual/asexual reproduction, self/cross-fertilization

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

- Theme 3: Sustainable interactions between species: parasitism, mutualism, coevolution

- Theme 4: Traces of evolutionary history in genomes, genomics of adaptation.

See the full page

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

See the full page

The objective of this EU is to demonstrate that biological diversity is functional:

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

2) at different organizational scales (from organisms to ecosystems). The lessons aim 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.

See the full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to highlight the existence of gene phylogenies within species phylogenies, the methods used to represent evolutionary histories in the form of trees, and the challenge of positional molecular homology through sequence alignment. The principles of phylogenetic inference methods are at the heart of this course unit. Distance methods highlight the difficulties of separating homology and homoplasy, and the need to construct models of character evolution. The cladistic approach with maximum parsimony illustrates, on the one hand, the use of bootstrapping to estimate the robustness of phylogeny nodes and, on the other hand, the impact of taxonomic sampling on the detection of multiple substitutions.

Probabilistic approaches are presented and explored in depth. The artifact of attraction to long branches leads to the introduction of probabilistic reasoning. The maximum likelihood method allows us to address likelihood calculation, model parameter estimation by optimality, the construction of different character evolution models, and model comparison. Bayesian inference introduces the distinction between density-based and optimality-based approaches. It then shows the a priori use of probability densities, the estimation of the posterior distributions of model parameters based on the data, their approximation by Markov chains with Monte Carlo techniques and Metropolis coupling (MCMCMC), the ignition and convergence phases, and the calculation and interpretation of the posterior probabilities of trees and clades. The importance of DNA, RNA, and protein sequence evolution models and their improvement is emphasized.

See the full page

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

During the module, we will discuss several evolutionary issues relevant to Evo-Devo approaches based on articles: the question of homology, the establishment and evolution of repeated structures, the genetic basis of development, and the links between genome evolution and form evolution. We will illustrate these concepts using examples from metazoans and the green lineage, and apply them to both large modern groups and populations.

See the full page

See the full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chain Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

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

See the full page

The courses present four aspects of conservation biology based on current scientific research in this discipline:  

1. Introduction to biodiversity conservation(BC): definition of conservation biology. Why conserve biodiversity? Who are the main players in BC and what role does science play in BC? 
2. Species conservation: Which species are priorities? How can species be conserved? How can we tell if a species is "well conserved"? 
3. Conserving spaces: Which spaces are priorities? How can spaces be conserved? 
4. Does conservation work?The importance of social acceptability and political commitment. The need for biodiversity indicators and measuring the impact of conservation. 

Students also carry out group work in which they present a BC project, focusing on the following questions: why, what, where, how, how much does it cost, and how can we know if it is effective? 

See the full page

The objectives of this EU are to explore key concepts related to climate change, illustrate important notions in ecology and evolution in light of climate change in many different ecosystems, and summarize the various scientific and societal issues and challenges posed by CC.

See the full page

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

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

See the full page

The overall objective is to present human evolutionary biology, proposing to use the tools of evolutionary biology to better understand human behavior and that observed in non-human primates in the context of their evolutionary history. Whether it be health, sociality, culture, local adaptations, language, morality, reproduction, or sexual preferences, the topics are addressed within the theoretical framework of evolutionary biology and ecology. Summary of course content: Anthropology, human sciences, and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of diet / Evolution of sociality in primates / Family ecology / Medicine, public health, and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See the full page

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

The module exposes students to various basic concepts and the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of modeling tools, ecophysiology, molecular biology, biochemistry, embedded electronics, etc.). Part of the training is based on specific discussions about the research approaches that can be used, the tools employed, and the limits of the inferences that can be made. Students will be asked to participate actively at these different levels, particularly through critical discussions of articles.

The topics covered range from exploring food supply strategies, partner 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 according to the sensitivity of the speakers and the topics covered (meaning and relationships between 'Animal Behavior', 'Ethology', Behavioral Ecology, etc.).

See the full page

The objective of this EU is to support students in finalizing their professional projects and preparing for life after their master's degree.

The EU is organized on a course-wide basis, with regular discussion sessions between the teaching team and students.

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The individual M2 internship lasts approximately 5 to 6 months and must be carried out, depending on the course concerned, 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 can be carried out in a local, national, or international organization, on a topic approved by the teaching team so as to fit in with the specific objectives of the program followed by the student.

Assessment: The internship is assessed during a public defense before a jury, during which the content of the thesis and the quality of the responses to the jury's questions are evaluated. The student's behavior and enthusiasm during the internship are assessed by the internship supervisor.

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