Evolutionary biology and ecology (DARWIN)

"General linear models with 1 or more explanatory random variables: from translating the figure that answers the biological question to the statistical model, i.e., taking into account many effects and knowing how to interpret them

general properties seen through regression and 1-factor ANOVA (R2, F, ddl, least squares, likelihood, diagnosis, validation, goodness of fit, interpretation of effect sizes); nested and cross-factor ANOVA, multiple regression (notion of parameter and effects, and interaction)

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

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The general objective is to consolidate the basic knowledge of ecology acquired by the students, and to give them the tools to mobilize it in an integrative way to interpret the functioning of ecological systems. The courses include: 1) lectures on the concepts of ecology from the population scale to macroecological scales, with examples of applications that place the discipline in the current ecological and societal context; 2) practical and directed work focused on tools (sampling strategies, modeling, data analysis); 3) field courses during which students are invited to ask themselves relevant scientific questions based on observation in a situation, and to mobilize their knowledge in order to respond to them in an argumentative manner.

Synthetic content of the EU :

- CM: History of the emergence of concepts in ecology; Population dynamics / metapopulations; Biotic interactions and food webs; Community ecology, meta-communities; Ecology of ecosystems / functional ecology; Notions of macroecology / biogeography; Global changes and ecosystem functioning;

- Field: Integrative Analysis of Ecosystem Functioning in Situations;

- TD/TP: sampling and experimental strategies in ecology; modeling in population/meta-population dynamics, community/meta-community ecology, food webs; biodiversity metrics (alpha, beta, etc)."

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"The general objective is to consolidate the students' bases in evolutionary biology, by approaching both (i) macro-evolutionary phenomena, and the general methods used for their analysis and (ii) micro-evolutionary processes by insisting on the population genetic approach. The objective of this course is to provide a common base of solid knowledge in evolutionary biology and to illustrate the applications of the discipline to the students' future fields of specialization. The teaching includes: 1) lectures on evolutionary concepts; 2) practical work in two main forms: 2a. sessions focused on the use of tools (phylogeny) and on the mathematical formalization of evolutionary processes (population genetics) as well as 2b: sessions built around group work, allowing students, depending on their career path and professional objectives, to go deeper into a particular theme (fundamental question or application of evolutionary biology)."

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English tutorials aimed at professional autonomy in the English language.

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"The phylogenetic tree is a central concept in biology for students in the fields of ""Biodiversity, Ecology & Evolution"", ""Biology Agrosciences"", and ""Eco-epidemiology"". To approach phylogeny, this UE is divided into two successive parts of 22,5h each: ""Phylogeny and Evolution (Basics)"" (HAB708B) and ""Phylogeny and Evolution (Advanced)"" (HAB714B).

The following knowledge will be taught:

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

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

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

(iv) Phylogenetic inference methods by distances [Advanced].

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

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

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

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

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Generalized linear mixed models + methodology and experimental protocols to take into account a biological reality: non-normal law and pseudo-replication

Protocol optimization, power and uncontrolled 1st order risk: variable transformation, polynomial regression, link function, likelihood, model selection

Deviance analysis and goodness of fit

Incorporation of blocks, repeated measurements over time, taking into account spatial and temporal correlation, over-dispersion

Graphical representation of predictions.

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The objective of this course is to provide the necessary basis in statistics to follow all the more elaborate modules of the curriculum, so it is a general refresher. Descriptive statistics are reviewed (quantile, polygon of cumulative frequencies, estimators from samples), simple tests are presented, essential graphs for univariate and multivariate data are presented, the general principle of a statistical test, the hypothesis plan, the notion of p-value, first and second species risk are presented. In practical exercises, 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 in the fields of ""Biodiversity, Ecology & Evolution"", ""Biology Agrosciences"", and ""Eco-epidemiology"". To approach phylogeny, this UE is divided into two successive parts of 22,5h each: ""Phylogeny and Evolution (Basics)"" (HAB708B) and ""Phylogeny and Evolution (Advanced)"" (HAB714B).

The following knowledge will be taught:

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

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

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

(iv) Phylogenetic inference methods by distances [Advanced].

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

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

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

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

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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) To propose a panorama of research themes in evolutionary genomics in the form of pedagogical seminars: molecular evolution, evolutionary genomics of endosymbioses, chromosomal evolution and molecular evolution.

3) Finally, the EU proposes a project of bioanalysis of an empirical dataset to understand the analysis in evolutionary genomics and to rub shoulders with the bioinformatics aspects increasingly developed in the discipline.

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The individual internship in M1 lasts about three months and must be carried out, depending on the course, in a research laboratory or a structure in the non-academic sector. It allows the student to acquire professional experience in the field of biodiversity, evolution or ecology. It can be carried out in a local, national, or international structure, on a subject validated by the teaching staff in order to meet the objectives of the course followed by the student.

Evaluation: The preparation of the internship is a graded exercise based on a written document and a defense of the internship project. The internship work is evaluated during a public defense before a jury during which the content of the thesis and the quality of the answers to the jury's questions are evaluated. The behavior and dynamism of the student during the internship are evaluated by the internship supervisor.

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"The objective of this course is to consolidate the students' knowledge of ecology and/or evolution by inviting them to define a research topic and question(s), by defining relevant hypotheses in an arguable manner, and by justifying a strategy for acquiring and analyzing data to test them.

Synthetic content of the EU:

- Independent tutored work: identification of a relevant scientific question; bibliographic synthesis allowing to realize the state of the art and to justify the scientific hypotheses; proposal and justification of a methodological approach (material and methods) to test the proposed hypotheses.

Type of topics:

The topics can be on any question identified by the students (in groups of 3/4), and validated by the teaching staff, and can be based on different approaches allowing to adjust to the expectations of the different courses. For example, students can propose a sampling strategy in the field or in experiments, a meta-analysis of data from the literature, an analysis of sequences retrieved from GenBank, an analysis of occurrence data retrieved from GBIF, etc.

In all cases, the projects must involve a real data acquisition strategy, identified, justified and described by the students in the material and method requested in M1S2, with a provisional timetable 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 The projects must also be financially realistic and propose a provisional budget, and must be able to be finalized in the time available in M2S3.

Methods of control of knowledge:

The teaching is based on a problem-based learning approach, and students are evaluated on the way they progress in building their approach (40% of CC), as well as on their ability to present and defend their project during a final oral (60% of the overall grade)."

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"This module presents table management and the link between multivariate and univariate: matrix manipulation and common operations; notion of projection and distance; translation of descriptive and univariate statistics with multiple regression/ACP/AFD as an example; (dis)similarity indices, distance; correlation"

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"The objective of this course is to complete the first semester's teaching by developing the problems related to the evolution of phenotypes and the main associated methodological approaches. The lectures 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 game theory formalization, adaptive dynamics, quantitative genetic approaches, and the work of confronting theoretical predictions with empirical data. Coursework 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 on Earth? What ecological, evolutionary and historical factors determine these patterns of biodiversity distribution? What are the changes induced by human activities on the global distribution of biodiversity? In this course, we will study the role of spatio-temporal variations in the global environment 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 at the planetary scale.

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- Firstly, to give students a base of knowledge and computer skills and thus provide them with a solid foundation for learning and using the bioinformatics tools used more specifically in evolution and ecology.

- Secondly, to make them aware of the need to produce reproducible results and to introduce them to the key concepts and tools for this.

- Thirdly, to make the students work on concrete examples that can be used during their master's course and their future professional life.

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"Darwin Field School" takes place over a week with the following objectives:

- Create a group dynamic and integration in the Master 2 DARWIN-BEE class.

- Analyze ecological issues in their technical, scientific and social dimensions (for example: reintroduction operations).

- To address the issues of biodiversity management in a humanized protected area.

- Oral presentation and confrontation of results to an assembly; assessment of the course.

Activities in Florac :

- Discover the landscapes of the Causse Méjean.

- Understand the specificities of the missions of the Cevennes National Park and its scientific policy of knowledge acquisition.

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

- Practice personal work in 3 sub-groups on different scientific and ethical themes.

Activities around Montpellier :

- To study bird migration and the ecosystems of the Mediterranean coastline.

- Practicing urban ecology.

- Discover the fauna of the Mediterranean scrublands, with daytime hikes along the Buèges (discovery of entomofauna) and evening hikes (bat and/or moth and nocturnal orthopterans evening)."

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The module covers the following fundamental topics in evolutionary biology: Micro evolution -Macro evolution, Fitness, Natural and sexual selves, Speciation. Other topics (mutation, epigenetics, evo-devo ...) are presented by the students themselves.

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The objective of this course is to accompany the student in the construction of his professional project and his search for an internship, while beginning to prepare his integration into professional life by an exhaustive and personal vision of possible career paths.

In concrete terms, meetings with different speakers allow the presentation of the doctoral thesis (presentation of the GAIA doctoral school, presentations by thesis students) and the professional environment targeted by the different courses (research professions and the non-academic sector). Activities specific to each pathway then help to better target the scientific fields most closely related to the students' professional projects. Lastly, the course includes practical sessions designed to prepare students to write scientific articles in English.

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The objective of this course is to design a research project on one of the major themes in ecology such as ecological niche, biogeography, networks of ecological interactions or functional diversity. A short reminder of the major theories and concepts in these major themes in ecology is presented by specialists in these themes. This review is followed by one or more examples illustrating the conceptual bases for formulating a relevant and new research question and how to answer it with different methodologies, especially experimental, from the speakers' research. After choosing one of these major themes, each student develops an original research project (of the size of an M2 internship), by conducting a bibliographic search and proposing a coherent experimental plan to test the hypotheses. This project is presented to the lecturers and the other students.

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

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

2) at different scales of organization (from organisms to the ecosystem). The lessons aim to explain how to approach this functional facet of diversity for the 10+ million organisms present on the surface of the planet, by taking examples in very or slightly anthropized environments.

See full page

The module addresses the theoretical and empirical advances of recent research in evolutionary genetics through some major issues:

- theme 1: genetic burden and evolution of reproductive systems: recombination, sex/sex, auto/allo fertilization

- theme 2 : Matching structures and their evolutionary consequences : kinship 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 the necessary skills to understand and use the concepts and methods on which the quantitative study of population phenomena is based. The main methods of analysis and modelling of these phenomena will be approached both from a theoretical point of view (formal calculations) and from a practical point of view (statistics, simulations), by means of examples exploring the different phylogenetic scales (microbial dynamics, invasive species, human demography), spatial (from local to global) and temporal (transient and permanent regimes, eco-evolutionary coupling), with a particular attention to heterogeneity (spatial, genetic or phenotypic) and randomness (stochasticity, uncertainties) characteristic of populations or inherent to their study.

See 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 present and past morphological diversity, and thus opens an important bridge between biology and paleontology.

During the module, we will discuss, based on articles, several evolutionary issues that are useful for Evo-Devo approaches: the question of homology, the question of the establishment and evolution of repeated structures, the genetic basis of development and the links between genome evolution and shape evolution. We will illustrate these notions from examples taken from metazoans and the green lineage, and will apply them to the scale of large current groups but also to populations.

See full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to recall the existence of gene phylogenies in species phylogenies, the ways of representing 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 the knowledge of this course. The distance methods allow to underline the difficulties of separating homology and homoplasy, and the necessity to build models of character evolution. The cladistic approach with maximum parsimony allows to illustrate on the one hand the use of bootstrap to estimate the strength of the nodes of phylogenies, and on the other hand the impact of taxonomic sampling to detect multiple substitutions.

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

See full page

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1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

See full page

The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / Evolution of sociality in primates / Family ecology / Medicine, public health and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

See full page

The courses present 4 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 actors in CB and the role of science in CB. 
2. Species conservation: What are the priority species? How to conserve species? How do you know if a species is "well conserved"? 
3. Space conservation: What are the priority spaces? How to conserve spaces? 
4. Does conservation work?Importance of social acceptability and political commitment. Need for biodiversity indicators and measuring the impact of conservation. 

Students also complete a group assignment in which they present a SA project around the questions: why, what, where, how, how much does it cost and how do we know if it is effective? 

See full page

The goals of this course are to deepen the key concepts related to climate change, to illustrate important concepts in ecology and evolution in the light of climate change, in many different ecosystems, and to synthesize the different scientific and societal questions and issues raised by CC.

See full page

Quantitative genetics is a discipline born at the beginning of the 20th century to understand the heredity of continuous traits, i.e. the majority of traits of agronomic (yield...) 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 relevant than ever at the beginning of the 21st century, with the advent of genomics (a factor of scientific progress provided that all evolutionary problems are not reduced to the fiction of a few Mendelian alleles with a strong effect), and the return in force of alternative models of heredity (epigenetics) that go beyond the sequence-centric vision inherited from classical molecular biology.

The aim of the module is to provide a culture of quantitative genetics sufficient to (i) understand the classical foundations of the discipline, manipulate the key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques for estimating 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 fits in with the classical Mendelian view.

See full page

The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / Evolution of sociality in primates / Family ecology / Medicine, public health and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See full page

Behavioral Ecology approaches the study of behavior from an evolutionary perspective to study the mechanisms, function, and contribution of behavior to evolutionary and ecological processes. The work carried out in Behavioral Ecology helps to understand other phenomena observed in other disciplines of life biology, because all animals, from unicellulars to the most complex vertebrates, exhibit behaviors.

The module allows students to be exposed to the different basic concepts, as well as to the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of tools from modeling, ecophysiology, molecular biology, biochemistry, embedded electronics...). Part of the training is based on specific discussions on the research approaches that can be used, the tools used and the limits of inferences that can be made. An active participation of the students will be required at these different levels, notably through critical discussions of articles.

The topics covered range from the exploration of food procurement strategies, mate choice, habitat choice, 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 sensibility of the speakers and the themes addressed (meaning and relations between 'Animal Behaviour', 'Ethology', Behavioral Ecology etc...).

See full page

The module addresses the theoretical and empirical advances of recent research in evolutionary genetics through some major issues:

- theme 1: genetic burden and evolution of reproductive systems: recombination, sex/sex, auto/allo fertilization

- theme 2 : Matching structures and their evolutionary consequences : kinship 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 full page

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

See full page

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

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

2) at different scales of organization (from organisms to the ecosystem). The lessons aim to explain how to approach this functional facet of diversity for the 10+ million organisms present on the surface of the planet, by taking examples in very or slightly anthropized environments.

See full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to recall the existence of gene phylogenies in species phylogenies, the ways of representing 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 the knowledge of this course. The distance methods allow to underline the difficulties of separating homology and homoplasy, and the necessity to build models of character evolution. The cladistic approach with maximum parsimony allows to illustrate on the one hand the use of bootstrap to estimate the strength of the nodes of phylogenies, and on the other hand the impact of taxonomic sampling to detect multiple substitutions.

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

See 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 present and past morphological diversity, and thus opens an important bridge between biology and paleontology.

During the module, we will discuss, based on articles, several evolutionary issues that are useful for Evo-Devo approaches: the question of homology, the question of the establishment and evolution of repeated structures, the genetic basis of development and the links between genome evolution and shape evolution. We will illustrate these notions from examples taken from metazoans and the green lineage, and will apply them to the scale of large current groups but also to populations.

See full page

See full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

See full page

The courses present 4 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 actors in CB and the role of science in CB. 
2. Species conservation: What are the priority species? How to conserve species? How do you know if a species is "well conserved"? 
3. Space conservation: What are the priority spaces? How to conserve spaces? 
4. Does conservation work?Importance of social acceptability and political commitment. Need for biodiversity indicators and measuring the impact of conservation. 

Students also complete a group assignment in which they present a SA project around the questions: why, what, where, how, how much does it cost and how do we know if it is effective? 

See full page

The goals of this course are to deepen the key concepts related to climate change, to illustrate important concepts in ecology and evolution in the light of climate change, in many different ecosystems, and to synthesize the different scientific and societal questions and issues raised by CC.

See full page

Quantitative genetics is a discipline born at the beginning of the 20th century to understand the heredity of continuous traits, i.e. the majority of traits of agronomic (yield...) 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 relevant than ever at the beginning of the 21st century, with the advent of genomics (a factor of scientific progress provided that all evolutionary problems are not reduced to the fiction of a few Mendelian alleles with a strong effect), and the return in force of alternative models of heredity (epigenetics) that go beyond the sequence-centric vision inherited from classical molecular biology.

The aim of the module is to provide a culture of quantitative genetics sufficient to (i) understand the classical foundations of the discipline, manipulate the key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques for estimating 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 fits in with the classical Mendelian view.

See full page

The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / Evolution of sociality in primates / Family ecology / Medicine, public health and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See full page

Behavioral Ecology approaches the study of behavior from an evolutionary perspective to study the mechanisms, function, and contribution of behavior to evolutionary and ecological processes. The work carried out in Behavioral Ecology helps to understand other phenomena observed in other disciplines of life biology, because all animals, from unicellulars to the most complex vertebrates, exhibit behaviors.

The module allows students to be exposed to the different basic concepts, as well as to the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of tools from modeling, ecophysiology, molecular biology, biochemistry, embedded electronics...). Part of the training is based on specific discussions on the research approaches that can be used, the tools used and the limits of inferences that can be made. An active participation of the students will be required at these different levels, notably through critical discussions of articles.

The topics covered range from the exploration of food procurement strategies, mate choice, habitat choice, 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 sensibility of the speakers and the themes addressed (meaning and relations between 'Animal Behaviour', 'Ethology', Behavioral Ecology etc...).

See full page

See full page

See full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

See full page

The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / Evolution of sociality in primates / Family ecology / Medicine, public health and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See full page

1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

See full page

The courses present 4 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 actors in CB and the role of science in CB. 
2. Species conservation: What are the priority species? How to conserve species? How do you know if a species is "well conserved"? 
3. Space conservation: What are the priority spaces? How to conserve spaces? 
4. Does conservation work?Importance of social acceptability and political commitment. Need for biodiversity indicators and measuring the impact of conservation. 

Students also complete a group assignment in which they present a SA project around the questions: why, what, where, how, how much does it cost and how do we know if it is effective? 

See full page

The goals of this course are to deepen the key concepts related to climate change, to illustrate important concepts in ecology and evolution in the light of climate change, in many different ecosystems, and to synthesize the different scientific and societal questions and issues raised by CC.

See full page

Quantitative genetics is a discipline born at the beginning of the 20th century to understand the heredity of continuous traits, i.e. the majority of traits of agronomic (yield...) 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 relevant than ever at the beginning of the 21st century, with the advent of genomics (a factor of scientific progress provided that all evolutionary problems are not reduced to the fiction of a few Mendelian alleles with a strong effect), and the return in force of alternative models of heredity (epigenetics) that go beyond the sequence-centric vision inherited from classical molecular biology.

The aim of the module is to provide a culture of quantitative genetics sufficient to (i) understand the classical foundations of the discipline, manipulate the key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques for estimating 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 fits in with the classical Mendelian view.

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The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / 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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Behavioral Ecology approaches the study of behavior from an evolutionary perspective to study the mechanisms, function, and contribution of behavior to evolutionary and ecological processes. The work carried out in Behavioral Ecology helps to understand other phenomena observed in other disciplines of life biology, because all animals, from unicellulars to the most complex vertebrates, exhibit behaviors.

The module allows students to be exposed to the different basic concepts, as well as to the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of tools from modeling, ecophysiology, molecular biology, biochemistry, embedded electronics...). Part of the training is based on specific discussions on the research approaches that can be used, the tools used and the limits of inferences that can be made. An active participation of the students will be required at these different levels, notably through critical discussions of articles.

The topics covered range from the exploration of food procurement strategies, mate choice, habitat choice, 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 sensibility of the speakers and the themes addressed (meaning and relations between 'Animal Behaviour', 'Ethology', Behavioral Ecology etc...).

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The module addresses the theoretical and empirical advances of recent research in evolutionary genetics through some major issues:

- theme 1: genetic burden and evolution of reproductive systems: recombination, sex/sex, auto/allo fertilization

- theme 2 : Matching structures and their evolutionary consequences : kinship 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 the necessary skills to understand and use the concepts and methods on which the quantitative study of population phenomena is based. The main methods of analysis and modelling of these phenomena will be approached both from a theoretical point of view (formal calculations) and from a practical point of view (statistics, simulations), by means of examples exploring the different phylogenetic scales (microbial dynamics, invasive species, human demography), spatial (from local to global) and temporal (transient and permanent regimes, eco-evolutionary coupling), with a particular attention to heterogeneity (spatial, genetic or phenotypic) and randomness (stochasticity, uncertainties) characteristic of populations or inherent to their study.

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

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

2) at different scales of organization (from organisms to the ecosystem). The lessons aim to explain how to approach this functional facet of diversity for the 10+ million organisms present on the surface of the planet, by taking examples in very or slightly anthropized environments.

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Phylogeny is a quest for evolutionary clues. The aim of this module is to recall the existence of gene phylogenies in species phylogenies, the ways of representing 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 the knowledge of this course. The distance methods allow to underline the difficulties of separating homology and homoplasy, and the necessity to build models of character evolution. The cladistic approach with maximum parsimony allows to illustrate on the one hand the use of bootstrap to estimate the strength of the nodes of phylogenies, and on the other hand the impact of taxonomic sampling to detect multiple substitutions.

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

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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 present and past morphological diversity, and thus opens an important bridge between biology and paleontology.

During the module, we will discuss, based on articles, several evolutionary issues that are useful for Evo-Devo approaches: the question of homology, the question of the establishment and evolution of repeated structures, the genetic basis of development and the links between genome evolution and shape evolution. We will illustrate these notions from examples taken from metazoans and the green lineage, and will apply them to the scale of large current groups but also to populations.

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1. Bayesian inference: Motivation and simple example. 

2. The likelihood. 

3. A detour to explore priors. 

4. Markov chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

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The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / 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 chains Monte Carlo methods (MCMC)

5. Bayesian analyses in R with the Jags software.  

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

7. Heterogeneity and multilevel models (aka mixed models. 

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The courses present 4 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 actors in CB and the role of science in CB. 
2. Species conservation: What are the priority species? How to conserve species? How do you know if a species is "well conserved"? 
3. Space conservation: What are the priority spaces? How to conserve spaces? 
4. Does conservation work?Importance of social acceptability and political commitment. Need for biodiversity indicators and measuring the impact of conservation. 

Students also complete a group assignment in which they present a SA project around the questions: why, what, where, how, how much does it cost and how do we know if it is effective? 

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The goals of this course are to deepen the key concepts related to climate change, to illustrate important concepts in ecology and evolution in the light of climate change, in many different ecosystems, and to synthesize the different scientific and societal questions and issues raised by CC.

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Quantitative genetics is a discipline born at the beginning of the 20th century to understand the heredity of continuous traits, i.e. the majority of traits of agronomic (yield...) 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 relevant than ever at the beginning of the 21st century, with the advent of genomics (a factor of scientific progress provided that all evolutionary problems are not reduced to the fiction of a few Mendelian alleles with a strong effect), and the return in force of alternative models of heredity (epigenetics) that go beyond the sequence-centric vision inherited from classical molecular biology.

The aim of the module is to provide a culture of quantitative genetics sufficient to (i) understand the classical foundations of the discipline, manipulate the key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques for estimating 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 fits in with the classical Mendelian view.

See full page

The general objective is to present human evolutionary biology, proposing to mobilize the tools of evolutionary biology in order to better understand human behaviors and those 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 themes are approached within the theoretical framework of evolutionary biology and ecology. Synthetic content of the course: Anthropology, human sciences and evolutionary biology / Evolution of cooperation / Cultural evolution / Evolution of food / Evolution of sociality in primates / Family ecology / Medicine, public health and evolution / Evolution of language / Evolutionary demography / The origins of equity.

See full page

Behavioral Ecology approaches the study of behavior from an evolutionary perspective to study the mechanisms, function, and contribution of behavior to evolutionary and ecological processes. The work carried out in Behavioral Ecology helps to understand other phenomena observed in other disciplines of life biology, because all animals, from unicellulars to the most complex vertebrates, exhibit behaviors.

The module allows students to be exposed to the different basic concepts, as well as to the multitude of tools that can be used (observations and experiments in natural populations or on captive individuals, comparative analyses, use of tools from modeling, ecophysiology, molecular biology, biochemistry, embedded electronics...). Part of the training is based on specific discussions on the research approaches that can be used, the tools used and the limits of inferences that can be made. An active participation of the students will be required at these different levels, notably through critical discussions of articles.

The topics covered range from the exploration of food procurement strategies, mate choice, habitat choice, 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 sensibility of the speakers and the themes addressed (meaning and relations between 'Animal Behaviour', 'Ethology', Behavioral Ecology etc...).

See full page

The module addresses the theoretical and empirical advances of recent research in evolutionary genetics through some major issues:

- theme 1: genetic burden and evolution of reproductive systems: recombination, sex/sex, auto/allo fertilization

- theme 2 : Matching structures and their evolutionary consequences : kinship 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 full page

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

See full page

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

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

2) at different scales of organization (from organisms to the ecosystem). The lessons aim to explain how to approach this functional facet of diversity for the 10+ million organisms present on the surface of the planet, by taking examples in very or slightly anthropized environments.

See full page

Phylogeny is a quest for evolutionary clues. The aim of this module is to recall the existence of gene phylogenies in species phylogenies, the ways of representing 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 the knowledge of this course. The distance methods allow to underline the difficulties of separating homology and homoplasy, and the necessity to build models of character evolution. The cladistic approach with maximum parsimony allows to illustrate on the one hand the use of bootstrap to estimate the strength of the nodes of phylogenies, and on the other hand the impact of taxonomic sampling to detect multiple substitutions.

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

See 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 present and past morphological diversity, and thus opens an important bridge between biology and paleontology.

During the module, we will discuss, based on articles, several evolutionary issues that are useful for Evo-Devo approaches: the question of homology, the question of the establishment and evolution of repeated structures, the genetic basis of development and the links between genome evolution and shape evolution. We will illustrate these notions from examples taken from metazoans and the green lineage, and will apply them to the scale of large current groups but also to populations.

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The objective of this course is to help students finalize their professional projects and prepare for the post-master's program.

The EU is organized at the level of the course, with regular discussion sessions between the teaching staff and the students.

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The individual M2 internship lasts approximately 5 to 6 months and must be carried out, depending on the course, in a research laboratory or a structure in the non-academic sector. It allows the student to acquire in-depth professional experience in the field of biodiversity, evolution or ecology. It can be carried out in a local, national, or international structure, on a subject validated by the teaching staff in order to meet the objectives of the course followed by the student.

Evaluation: The internship is evaluated during a public defense before a jury during which the content of the thesis and the quality of the answers to the jury's questions are evaluated. The behavior and dynamism of the student during the internship are evaluated by the internship supervisor.

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