MASTER'S DEGREE IN BIODIVERSITY, ECOLOGY, AND EVOLUTION

This EU will take the form of a series of a dozen conferences/seminars on current research topics in vertebrate paleontology and evolutionary biology; biodiversity and paleobiodiversity of continental ecosystems (animal); topographic and climatic barriers vs. dispersion and vicariance; community structure, food chains over time, and paleoguilds; the role of geodynamics and contingency (crises). The main objective is to acquire a good understanding of the current research topics/areas in the paleontological/evolutionary community."

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This course will take the form of a one-week field internship on site (with accommodation provided), where possible. The internship locations may change from year to year depending on discoveries and/or partnership proposals (public/private). This internship may therefore take different forms, with a "prospecting" approach and therefore a mobile fieldwork component, or a more "excavation site" approach and therefore a fixed component. In all cases, the various objectives listed below will be addressed in order to make the most of this week in the field and ensure that the various techniques are mastered as well as possible.

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In this course, we will address the main theoretical concepts of evolutionary processes through the fossil record. We will discuss how to reconcile microevolutionary and macroevolutionary mechanisms. The concepts covered will be: species and intraspecific variability, speciation and the pace of evolution, adaptive radiation (ecological speciation) in the fossil record, targeted extinctions (migrant-native competition) or mass extinctions (major biological crises), evolutionary modalities (anagenesis and saltationism) observed in the fossil record, and a comprehensive review of microevolutionary mechanisms.

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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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This course provides the necessary tools for data analysis in paleontology.

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"The objective is to analyze the phylogenetic, developmental, and functional constraints that may have governed the morphological changes observable in the fossil record. The phylogenetic approach will be addressed using reconstruction methods applicable to fossils (parsimony; cladistic analysis). Developmental and functional approaches (mainly odontology) will be illustrated by various methodologies developed on the Montpellier campus (in particular X-ray microtomography). A critical review of reference articles in the field will be followed by an oral presentation and a question-and-answer session."

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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

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.

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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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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.

See the full page

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.

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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). 

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.).

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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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https://www.evobio.eu/summer-school

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Each year, teachers will suggest a number of topics, from which students will choose (the list will be neither binding nor exhaustive: any topic that relates to evolution is fair game). Working in groups of two or three people, the students will be responsible for presenting the topic they have chosen. Each person in a group should participate equally in these presentations. Each group will be given a small selection of recent papers that they will use to begin to explore the topic, or the groups will themselves propose pertinent papers. Among these, the group will distribute (one week before the class session) one-two papers that everyone should read before class. The group will be responsible for presenting the topic to the rest of the class and leading discussion of it. The group presentation should explain why the topic is interesting and present the state of the art, outlining points of controversy and defining big open questions. The presentation format will be defined by the group, keeping in mind that it should open discussions. For the last session(s) at the end of the course, students will give short individual presentations providing a recap of some aspect(s) of another group's topic. In addition to the main hot topic presentations, there will be a brief 'writing summaries' exercise at the beginning of the course, and regular "news & views" briefings of recent articles picked by the students from journals of their choice.

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https://www.umontpellier.fr/en/research

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Starting from scratch for analyzing biological data: describing, testing, and modeling simple experimental protocols;

Getting to know fundamental properties of linear models dealing with simple regressions and simple ANOVAs;

Incorporating into models the essence of biological data: collinearity, dependence, spatial structure, laws that are not normal....

Representing data and results from models.

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Modeling is a methodology that is frequently used in biological sciences nowadays, in particular in ecological and evolutionary studies. However, models usually frighten students. The aim of this initiation is to show that modeling is by no means more inaccessible than other techniques in biology. The goal is to give students a feel for how a model is constructed, to be able to spot the key assumptions behind a result, and to test their validity. The course will seek to familiarize students with several basic modeling techniques and tools.

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This one-week course will be offered at least in winter 2020 (and in subsequent years if independent funding can be secured). It will be organized as a retreat during which students will write grant proposals on evolutionary biology topics in small groups.

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The course discusses cases where evolutionary biology-based implementations provide invaluable insight into applied issues such as vector control, conservation biology, or fish stock management.

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"The objectives of this course are threefold: (i) to remind students of the theoretical bases of some essential concepts of population genetics theory; (ii) to detail some "classical" inference methods (e.g., F-statistics) and more "modern" approaches (based, e.g., on coalescent theory); (iii) to show how demographic history may be inferred from the analysis of genetic polymorphisms."

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The objective of this course is to provide the theoretical background for understanding, and potentially being able to use and apply the principles of how selection will affect the evolution of populations. Y. Michalakis describes the basics of selection theory and shows with elementary algebra that it is possible to derive some fundamental results in Population Genetics, such as Fisher’s Fundamental Theorem. He also gives an introduction to mutation-selection balance and two-locus theory. The latter topics are put into perspective in the courses by T. Lenormand on the evolution of sexual reproduction, migration, and local adaptation. T. Lenormand also presents the theory that allows understanding the dynamics of adaptation. G. Martin's courses explain how stochastic effects interact with selection to influence the fate of adaptive mutations.

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https://www.evobio.eu/semester-3-4

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https://www.evobio.eu/summer-school

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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 aim of this EU is to understand the adaptive biology of organisms by considering individual and population responses to environmental variations. Concrete examples in animal evolutionary ecophysiology will be discussed in the context of global change. The responses of organisms and populations to abiotic parameters (such as temperature, salinity, oxygen availability, pollutants) will be considered, as well as their interactive effects. The course unit will demonstrate the involvement of physiological mechanisms in ecology, from phenotypic and cognitive processes at the intra-individual level to functional variants between individuals and between species. The concepts of intraspecific variability, phenotypic plasticity, and transgenerational effects will also be addressed. This course unit will be illustrated by examples of phenotypic trait analysis (including behavior) within populations. Links with genetic and epigenetic markers will also be discussed. Different approaches (-omics vs. gene/protein target), several experimental designs, and various scales of biological organization will be considered (molecule, gene, phenotype, individual, population, species).

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This module provides an introduction to ethnobotany and ethnoecology in order to understand the material and immaterial dimensions of the relationships between humans and their environment, with a particular focus on the plant world. We will focus in particular on local naming and classification systems, perceptions and representations of nature, resource management practices and uses, and biocultural, ecological, and evolutionary interactions. Ethnobotany and ethnoecology are disciplines at the interface of anthropology, botany, and ecology, which may also borrow tools and concepts from linguistics, archaeology, geography, and agronomy. This module complements the "Ethnoecology and Sustainable Development" module (Master 2) by providing the theoretical and methodological foundations of ethnobotany.

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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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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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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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ORPAL is a course unit in APP (1/3 fieldwork and 2/3 practical work in the laboratory). The work, carried out in pairs or groups of three under the supervision of a mentor, covers the entire research process, from defining the problem, sampling in the field, data acquisition, to interpretation, writing a scientific article (see https://biologie-ecologie.com/exemples-travaux/), and oral presentation of the results.

ORPAM takes place during the first weeks of teaching. This course begins with a three-day field school (24 hours - orientation course) and continues with a mini laboratory course (24 hours). The course ends with the writing of a popular science article and an oral presentation of the results.

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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 objective of this EU is to enable the implementation of projects defined within the framework of the M1S2 EU project.

Summary of EU content:

- Independent work supervised by student groups: readjustment of project objectives and methodology if necessary, data acquisition, ecological and/or evolutionary analyses and interpretations according to the provisional schedule defined in M1S2, presentation of results at a joint symposium for the different courses.

Assessment methods:

As with the EU M1 project, the EU uses a problem-based learning approach. Students are therefore assessed on an ongoing basis on their progress in completing their project (40% of the final grade), then at the end of the semester on their ability to present the results of their project and discuss them during an oral presentation at a general feedback symposium (60% of the final grade).

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The educational objective of this teaching unit is to reposition the major soil types on a global scale, explain their formation, and identify the mineral phases or main abiotic factors likely to regulate biological activity in soils. Based on this analysis, the various soil organisms (microorganisms, micro-, meso- and macrofauna) will be presented, along with their relationships, in order to reposition the cycle of organic matter and mineral elements in the soil at different temporal and spatial scales. The concepts of recycling, biogeochemical cycles and community assembly rules will also be addressed. This course unit is organized around lectures and conferences, as well as tutorials and fieldwork.

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Ecophysiology is a discipline at the interface between organism biology and ecology. Integrative ecophysiology focuses more specifically on the issue of scaling. In other words, this course aims to illustrate how the study of acclimatization/adaptation mechanisms at the individual (or even sub-individual) level can explain population structure, species distribution, and ecosystem functioning. The responses of organisms and populations to the main structuring abiotic parameters (such as temperature, salinity, oxygen availability, pollutants) will be considered, as well as their interactive effects. The role of interactions between organisms will also be addressed. In this course unit, animals, plants, and microorganisms will be considered, and different types of approaches will be illustrated: field observations, in situ or laboratory experiments.

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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.

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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.

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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). 

See the full page

The module aims to provide theoretical and practical knowledge of statistical analyses of spatial and temporal constraints: classification and ordination under constraints, '2-table ordination methods and statistical tests: canonical analyses (AFD, CCA, RDA, CAP), 'statistical tests on distance matrices, matrix comparison (PERMANOVA, Mantel, Procrustes)

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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? 

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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.

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"The content of this course unit consists of three main parts: I - Physical characterization and biogeochemical cycles of coastal marine ecosystems II - Biodiversity and functioning of coastal marine ecosystems III - Coastal and maritime law; uses, conflicts, and integrated management of the coastal zone. This course offers students a systemic approach to the study of coastal marine ecosystems from a highly multidisciplinary perspective. The physical structure of these ecosystems will be addressed through courses on their geomorphology and hydrology, with a particular focus on water connections with the open sea and their catchment areas. Their biogeochemistry will be addressed, in particular to describe carbon and nutrient flows through water and sediment compartments. Several aspects of their biodiversity will be illustrated to describe the importance of these ecosystems as habitats for dependent species, with a particular focus on the role of this biodiversity in their functioning. The coastal zone is densely populated by humans (40% of the world's population). Particular attention will be paid to human uses (e.g., aquaculture) and their territorial planning, including the assessment of their ecosystem services in an economic context, management and protection measures (e.g., Marine Protected Areas, Natura 2000), and professionals involved in the management of these environments will present concrete feedback. Finally, the implications of maritime law for the management of coastal areas will be taught. "

See the full page

The module covers topics related to identifying, quantifying, and modeling interactions between climate, marine species, and their exploitation.

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.).

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The objective of this resolutely transdisciplinary course is to provide students with the skills needed for the effective management and relevant use of data of various origins and types, particularly those with a spatial component. The course consists of three complementary and successive sections. The first addresses the challenges inherent in data compilation and the solutions provided by database management systems (DBMS): from database design to queries. The second focuses on geographic information systems (GIS): from cartographic representation to geoprocessing. Finally, the third axis presents the diversity of spatial analysis tools that enable the quantitative exploitation of spatial data, whether metrics or statistical tests.

See the full page

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The educational objective of this teaching unit is to reposition the major soil types on a global scale, explain their formation, and identify the mineral phases or main abiotic factors likely to regulate biological activity in soils. Based on this analysis, the various soil organisms (microorganisms, micro-, meso- and macrofauna) will be presented, along with their relationships, in order to reposition the cycle of organic matter and mineral elements in the soil at different temporal and spatial scales. The concepts of recycling, biogeochemical cycles and community assembly rules will also be addressed. This course unit is organized around lectures and conferences, as well as tutorials and fieldwork.

See the full page

Ecophysiology is a discipline at the interface between organism biology and ecology. Integrative ecophysiology focuses more specifically on the issue of scaling. In other words, this course aims to illustrate how the study of acclimatization/adaptation mechanisms at the individual (or even sub-individual) level can explain population structure, species distribution, and ecosystem functioning. The responses of organisms and populations to the main structuring abiotic parameters (such as temperature, salinity, oxygen availability, pollutants) will be considered, as well as their interactive effects. The role of interactions between organisms will also be addressed. In this course unit, animals, plants, and microorganisms will be considered, and different types of approaches will be illustrated: field observations, in situ or laboratory experiments.

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

The objective of this resolutely transdisciplinary course is to provide students with the skills needed for the effective management and relevant use of data of various origins and types, particularly those with a spatial component. The course consists of three complementary and successive sections. The first addresses the challenges inherent in data compilation and the solutions provided by database management systems (DBMS): from database design to queries. The second focuses on geographic information systems (GIS): from cartographic representation to geoprocessing. Finally, the third axis presents the diversity of spatial analysis tools that enable the quantitative exploitation of spatial data, whether metrics or statistical tests.

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 module aims to provide theoretical and practical knowledge of statistical analyses of spatial and temporal constraints: classification and ordination under constraints, '2-table ordination methods and statistical tests: canonical analyses (AFD, CCA, RDA, CAP), 'statistical tests on distance matrices, matrix comparison (PERMANOVA, Mantel, Procrustes)

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

"The content of this course unit consists of three main parts: I - Physical characterization and biogeochemical cycles of coastal marine ecosystems II - Biodiversity and functioning of coastal marine ecosystems III - Coastal and maritime law; uses, conflicts, and integrated management of the coastal zone. This course offers students a systemic approach to the study of coastal marine ecosystems from a highly multidisciplinary perspective. The physical structure of these ecosystems will be addressed through courses on their geomorphology and hydrology, with a particular focus on water connections with the open sea and their catchment areas. Their biogeochemistry will be addressed, in particular to describe carbon and nutrient flows through water and sediment compartments. Several aspects of their biodiversity will be illustrated to describe the importance of these ecosystems as habitats for dependent species, with a particular focus on the role of this biodiversity in their functioning. The coastal zone is densely populated by humans (40% of the world's population). Particular attention will be paid to human uses (e.g., aquaculture) and their territorial planning, including the assessment of their ecosystem services in an economic context, management and protection measures (e.g., Marine Protected Areas, Natura 2000), and professionals involved in the management of these environments will present concrete feedback. Finally, the implications of maritime law for the management of coastal areas will be taught. "

See the full page

The module covers topics related to identifying, quantifying, and modeling interactions between climate, marine species, and their exploitation.

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

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 module aims to provide theoretical and practical knowledge of statistical analyses of spatial and temporal constraints: classification and ordination under constraints, '2-table ordination methods and statistical tests: canonical analyses (AFD, CCA, RDA, CAP), 'statistical tests on distance matrices, matrix comparison (PERMANOVA, Mantel, Procrustes)

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

"The content of this course unit consists of three main parts: I - Physical characterization and biogeochemical cycles of coastal marine ecosystems II - Biodiversity and functioning of coastal marine ecosystems III - Coastal and maritime law; uses, conflicts, and integrated management of the coastal zone. This course offers students a systemic approach to the study of coastal marine ecosystems from a highly multidisciplinary perspective. The physical structure of these ecosystems will be addressed through courses on their geomorphology and hydrology, with a particular focus on water connections with the open sea and their catchment areas. Their biogeochemistry will be addressed, in particular to describe carbon and nutrient flows through water and sediment compartments. Several aspects of their biodiversity will be illustrated to describe the importance of these ecosystems as habitats for dependent species, with a particular focus on the role of this biodiversity in their functioning. The coastal zone is densely populated by humans (40% of the world's population). Particular attention will be paid to human uses (e.g., aquaculture) and their territorial planning, including the assessment of their ecosystem services in an economic context, management and protection measures (e.g., Marine Protected Areas, Natura 2000), and professionals involved in the management of these environments will present concrete feedback. Finally, the implications of maritime law for the management of coastal areas will be taught. "

See the full page

The module covers topics related to identifying, quantifying, and modeling interactions between climate, marine species, and their exploitation.

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 is to master the modeling and statistical analysis of ecosystem data. Students will need to be able to model complex systems (e.g., plants in a cultivated ecosystem, population dynamics, lake ecosystems). They will also need to know what type of statistical model to use for processing ecological data and how to interpret it.

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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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This EU addresses questions surrounding ecosystem management from a social science perspective, particularly that of "science studies." It aims to contribute to the development of a general culture related to the relationship between ecological sciences and societies, and to equip participants with the tools to analyze social issues and underlying socio-scientific controversies. The first part of the course provides the conceptual and methodological framework necessary to present a reflective tool for analyzing the roles of actors and arguments (epistemological, axiological) involved in socio-scientific controversies, and illustrates this tool with current examples. Subsequently, thematic presentations by researchers in ecology illustrate a variety of issues surrounding ecological sciences and serve as a basis for students to apply and acquire the reflective analysis tool. Students are thus assessed on their ability to use this analytical framework to take an individual and reasoned position in controversies related to ecological sciences.

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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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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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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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Based on ecological concepts and methods, this course unit aims to introduce students to historical ecology (the study of interactions between humans and their environment over varying periods of time) and its main applications in paleoecology and environmental sciences: climate change, fluctuations in biodiversity, vegetation transformation, forest dynamics, disturbance ecology, bioarchaeology, etc. ORPAL is an APP course (1/3 fieldwork and 2/3 laboratory work). The work, carried out in pairs or groups of three under the supervision of a mentor, covers the entire research process, from defining the problem field sampling, data acquisition, to interpretation, writing a scientific article (see https://biologie-ecologie.com/exemples-travaux/), and oral presentation of the results. ORPAM takes place during the first weeks of the academic year. This course unit begins with a three-day field school (24 hours - integration course) and continues with a mini laboratory course (24 hours). The course unit ends with the writing of a popular science article and an oral presentation of the results.

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The EU's objectives are twofold. On the one hand, it aims to retrace all the major stages in the history of organisms on Earth since its birth. Topics such as the emergence of life, the colonization of continents, the emergence of angiosperms, glacial/interglacial cycles, and the domestication of plants will be addressed. Secondly, it aims to show how paleoecology fits into the modern world, whether in terms of methodological developments (geochemistry, optical microscopy, electron microscopy, X-ray microscopy, etc.), climate change prediction models, ecosystem management in the context of global change, or developments in biotechnology.  The EU will mainly be organized into lectures (TD), each given by a specialist in the subject.

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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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Teaching unit aimed at linking theoretical ecology, its operational implementation, and territorial issues as seen by societal actors. Built on a format combining theoretical courses covering the elements necessary for understanding field issues (ecosystem dynamics, anthropization, socio-ecosystem resilience, in situ conservation, etc.), this teaching unit includes several field blocks (each consisting of a preparatory tutorial/practical and an "active" field trip). The territories visited will provide an opportunity to meet members of society (managers, elected officials, associations, shepherds, etc.) whose position allows us to understand how ecological issues govern their actions and how, in turn, their actions impact biodiversity, its dynamics, and its distribution.

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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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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 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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The objective of this EU is to enable the implementation of projects defined within the framework of the M1S2 EU project.

Summary of EU content:

- Independent work supervised by student groups: readjustment of project objectives and methodology if necessary, data acquisition, ecological and/or evolutionary analyses and interpretations according to the provisional schedule defined in M1S2, presentation of results at a joint symposium for the different courses.

Assessment methods:

As with the EU M1 project, the EU uses a problem-based learning approach. Students are therefore assessed on an ongoing basis on their progress in completing their project (40% of the final grade), then at the end of the semester on their ability to present the results of their project and discuss them during an oral presentation at a general feedback symposium (60% of the final grade).

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This EU focuses on analyzing the impact of humans on the climate and the environment.

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Present different methodological approaches in an applied context, from data acquisition to interpretation. Each approach is covered in half a day (3 hours), addressing data acquisition methods (1.5 hours of practical work) and interpretation of results (1.5 hours of tutorials).

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"The aim of this EU is to present and explain the concepts, issues, operational approach in the field and in the laboratory, and methodological and analytical strategies used to infer and reconstruct fluctuations in wild and human-exploited biodiversity over time. It draws on empirical and modeled data sets covering ecology, paleoecology, paleobiogeography, archaeobiology, archaeology, and paleoethnobiology. Particular attention will be paid to:

- the functional role of ecological disturbances such as fires in vegetation cover transformations;

- the impact of changes in human societies on the dynamics of forest ecosystems;

- the exploitation, cultivation/breeding, and domestication of plants and animals based on the study of modern and bioarchaeological data. "

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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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In this course, we will address the main theoretical concepts of evolutionary processes through the fossil record. We will discuss how to reconcile microevolutionary and macroevolutionary mechanisms. The concepts covered will be: species and intraspecific variability, speciation and the pace of evolution, adaptive radiation (ecological speciation) in the fossil record, targeted extinctions (migrant-native competition) or mass extinctions (major biological crises), evolutionary modalities (anagenesis and saltationism) observed in the fossil record, and a comprehensive review of microevolutionary mechanisms.

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The objective of this resolutely transdisciplinary course is to provide students with the skills needed for the effective management and relevant use of data of various origins and types, particularly those with a spatial component. The course consists of three complementary and successive sections. The first addresses the challenges inherent in data compilation and the solutions provided by database management systems (DBMS): from database design to queries. The second focuses on geographic information systems (GIS): from cartographic representation to geoprocessing. Finally, the third axis presents the diversity of spatial analysis tools that enable the quantitative exploitation of spatial data, whether metrics or statistical tests.

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The educational objective of this teaching unit is to reposition the major soil types on a global scale, explain their formation, and identify the mineral phases or main abiotic factors likely to regulate biological activity in soils. Based on this analysis, the various soil organisms (microorganisms, micro-, meso- and macrofauna) will be presented, along with their relationships, in order to reposition the cycle of organic matter and mineral elements in the soil at different temporal and spatial scales. The concepts of recycling, biogeochemical cycles and community assembly rules will also be addressed. This course unit is organized around lectures and conferences, as well as tutorials and fieldwork.

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"The objective is to analyze the phylogenetic, developmental, and functional constraints that may have governed the morphological changes observable in the fossil record. The phylogenetic approach will be addressed using reconstruction methods applicable to fossils (parsimony; cladistic analysis). Developmental and functional approaches (mainly odontology) will be illustrated by various methodologies developed on the Montpellier campus (in particular X-ray microtomography). A critical review of reference articles in the field will be followed by an oral presentation and a question-and-answer session."

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Land use changes are responsible for approximately 10% of anthropogenic carbon dioxide emissions. Tropical forest ecosystems can contribute to both pillars of addressing global warming, namely mitigation and adaptation:

-Tropical forests and plantations are important potential carbon sinks, their biomass can provide energy as a substitute for fossil fuels, while reducing deforestation and forest degradation and improving forest management (REDD+) can significantly reduce anthropogenic GHG emissions.

-The ability of human societies that are still predominantly rural to adapt to climate change depends in part on the state of available natural resources, while the necessary adaptation of tropical ecosystems to climate change can be facilitated by human intervention.

As part of the implementation of the United Nations Framework Convention on Climate Change, mechanisms such as the Clean Development Mechanism (CDM) and REDD+, voluntary markets, and ecosystem-based adaptation provide new opportunities for tropical forestry, as well as potential leverage for protecting or restoring tropical forests. The module provides an understanding of the basic concepts of climate change, the role of tropical ecosystems in the global carbon cycle, and technical, political, and economic responses to climate change issues.

Module content:

This module provides basic knowledge on topics such as the carbon cycle, the mechanisms and consequences of climate change, and the technical and political measures for mitigating and adapting to this change. The potential of tropical agroecosystems is assessed on the basis of scientific studies and existing operational projects.

Teaching and learning methods:

-Classes (18 hours)

-TD (3 hours).

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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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1. "The way in which the modern West represents nature is the least well-shared thing in the world" (Descola, 2005, p. 56). According to anthropologist Philippe Descola, the category of "Nature," as a reality separate from the human world, is an invention of Europeans that is only one of the possibilities available to societies to account for the living and non-living beings that surround them.

While Philippe Descola contributes to renewing questions about society-environment relations, he nevertheless draws on a long tradition in the humanities and social sciences. Numerous works already explore the various forms of knowledge and social organization to which these relations give rise: ethnoscience, anthropology of technology, economic anthropology, ethnoecology, sociology of science and technology, etc.

This issue is far from being confined to the academic sphere. It also attracts the interest of conservationists (biodiversity, natural resources, etc.) and industry (pharmacology). It also mobilizes so-called "indigenous" populations who are demanding, both locally and internationally, access to resources and the preservation of intangible heritage.

2. Located at the intersection of social sciences and life sciences, these disciplines analyze how human societies use plants, animals, and other components of the environment, but also how their conceptions and representations of their environment(s) guide these uses. This research also explores how human societies organize themselves, perpetuate themselves, change to adapt to new contexts (globalization, global changes), and transmit knowledge about their relationships with nature.

For a long time, these disciplines focused more specifically on the interrelationships between so-called "traditional" societies and their immediate environment. Subsequently, beginning in the 1970s, researchers reconsidered the distinction between so-called "traditional" and "modern" societies in order to better address new contemporary environmental and social transformations.

On the one hand, even the most isolated local communities are affected by events that are decided and take place at different levels (international conventions, economic crises). Their immediate environment is also affected by global phenomena (climate change, erosion of biodiversity, etc.). In turn, their actions can also have international ecological, social, and economic repercussions, for example when these societies organize to bring their demands to international arenas.

On the other hand, modern societies' relationship with their environment is being reconfigured in light of the fact that our planet is becoming increasingly "artificialized" and threatened by serious disruptions and crises. The place of fauna and flora is being reconsidered and is the subject of controversy regarding their rights. Furthermore, the dawn of a new geological era, the Anthropocene, is being invoked to challenge both the natural sciences and the humanities and social sciences on the need to take a different approach to the shared history of the environment and societies.

3. The work of scientists and engineers is being viewed in a new light. In this regard, a new scientific project in the humanities and social sciences aims to reconsider the role of "non-humans" and calls for the development of analytical categories other than those of Nature and Culture. New scales and methods of investigation are also being considered for analyzing global processes.

These recent changes in scale invite researchers in the humanities and social sciences to (re)consider their approach through a reflexive lens: they are no longer mere observers, but can also be active participants in processes, even when they are not directly involved in a social movement.

4. The objective of this module is to introduce these different scientific and operational fields. It aims to provide students with reference points and food for thought, enabling them to develop scientific questions on the relationship between society and the environment, with a view to reflecting on how to address current environmental and social issues. The varied geographical and disciplinary experiences of the speakers will illustrate the approach through a wide range of ecosystem types, sociocultural contexts, and themes. In the time available, we do not claim to cover all themes, approaches, and methods exhaustively. Any student wishing to study this field in greater depth will need to undertake more in-depth training.

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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.

See the full page

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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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)

See the full page

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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This teaching unit is part of a pre-professionalization program. It aims to encourage students to think about their career plans through meetings with professionals in the field of science communication, involvement in science communication projects at the interface between the worlds of research and secondary education (helping middle school classes to carry out projects on environmental education and sustainable development), and analysis of projects developed by Master's 2 students.

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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.

See the full page

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 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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Mediation (scientific or otherwise) increasingly relies on digital tools for disseminating information, which make it possible to reach a wide audience very quickly. These tools are numerous and diverse, and it is difficult to provide a simple overview of them all. Nevertheless, the vast majority of job and internship offers in the field of mediation require knowledge of how to use these digital mediation tools.

The aim of this course unit will therefore be to present the main digital mediation tools and introduce students interested in scientific mediation to their use. The course unit will also provide an opportunity to discuss the importance of sourcing and verifying data at a time when falsehoods and even lies are becoming increasingly prevalent.

The first part of the course will take the form of tutorials/practical sessions covering the main digital tools used in science communication. Examples posted online by various communication organizations will be analyzed in order to identify their strengths and weaknesses.

The second part of the course will focus on practical application. Students will visit scientific outreach organizations (temporary or permanent) and will be required to write reports using digital scientific outreach tools. In particular, one of the reports will focus on the scientific activities of the Biology and Ecology Department and will be posted on the department's website.

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