ECTS
12 credits
Component
Faculty of Science
List of courses
Your choice: 1 of 6
CHOICE2
4 creditsYour choice: 1 of 2
Bayesian approach to variability
2 creditsHuman evolutionary biology
2 credits
Choice of 6 out of 6
Bayesian approach to variability
2 creditsConservation Biology
2 creditsImpacts of climate change on organisms, ecosystems and
2 creditsQuantitative evolutionary genetics
2 credits12hHuman evolutionary biology
2 creditsBehavioral ecology
2 credits6h
Genetics and Evolutionary Genomics 2
4 credits15hPopulations, Randomness & Heterogeneity
4 creditsFunctional diversity: from organisms to the ecosystem
4 credits9hIn-depth phylogeny: methods and application in evolution
Evolution-Development
4 credits
Bayesian approach to variability
ECTS
2 credits
Component
Faculty of Science
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.
Human evolutionary biology
ECTS
2 credits
Component
Faculty of Science
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.
Bayesian approach to variability
ECTS
2 credits
Component
Faculty of Science
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.
Conservation Biology
ECTS
2 credits
Component
Faculty of Science
The courses present 4 aspects of Conservation Biology based on current scientific research in this discipline:
- 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.
- Species conservation: What are the priority species? How to conserve species? How do you know if a species is "well conserved"?
- Space conservation: What are the priority spaces? How to conserve spaces?
- 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?
Impacts of climate change on organisms, ecosystems and
ECTS
2 credits
Component
Faculty of Science
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.
Quantitative evolutionary genetics
ECTS
2 credits
Component
Faculty of Science
Hourly volume
12h
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.
Human evolutionary biology
ECTS
2 credits
Component
Faculty of Science
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.
Behavioral ecology
ECTS
2 credits
Component
Faculty of Science
Hourly volume
6h
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...).
Genetics and Evolutionary Genomics 2
ECTS
4 credits
Component
Faculty of Science
Hourly volume
15h
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.
Populations, Randomness & Heterogeneity
ECTS
4 credits
Component
Faculty of Science
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.
Functional diversity: from organisms to the ecosystem
ECTS
4 credits
Component
Faculty of Science
Hourly volume
9h
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.
In-depth phylogeny: methods and application in evolution
Component
Faculty of Science
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.
Evolution-Development
ECTS
4 credits
Component
Faculty of Science
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.