M1 - Functional ecology and conceptualization of terrestrial and aquatic ecosystems (EcoSystèmes)

"General linear models with 1 or more random explanatory variables: from the translation of 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 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 ANOVAs)".

See full page

The general aim is to consolidate the ecological foundations acquired by students, and to give them the tools to mobilize them in an integrative way to interpret the functioning of ecological systems. The course includes: 1) lectures covering the concepts of ecology from population to macro-ecological scales, with examples of applications that place the discipline in the current ecological and societal context; 2) practical work and tutorials focusing on tools (sampling strategies, modelling, data analysis); 3) field courses in which students are invited to ask themselves relevant scientific questions based on observation in a given situation, and to mobilize their knowledge to answer them in a reasoned way.

Summary content of the EU :

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

- Field: Integrative analysis of ecosystem functioning in real-life situations ;

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

See full page

"The overall aim is to consolidate students' evolutionary biology foundations, covering both (i) macro-evolutionary phenomena, and the general methods used to analyze them, and (ii) micro-evolutionary processes, with an emphasis on the population genetics approach. The aim of this course is both to provide a common foundation of solid knowledge in evolutionary biology, and to illustrate the applications of the discipline to students' future fields of specialization. Teaching includes: 1) lectures on evolutionary concepts; 2) practical work in two main forms: 2a. sessions focusing on the use of tools (phylogeny) and on the mathematical formalization of evolutionary processes (population genetics), and 2b: sessions built around group work, enabling students, depending on their career path and professional objectives, to delve deeper into a particular theme (fundamental question or application of evolutionary biology)."

See full page

English TD courses aimed at professional autonomy in the English language.

See full page

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

The ORPAM program begins in the first weeks of teaching. It begins with a 3-day field school (24h - integration internship) and continues with a mini-laboratory internship (24h). The course ends with the writing of a popular scientific article and an oral presentation of the results.

See full page

See full page

Generalized linear mixed models + methodology and experimental protocols to take account of biological reality: non-normal distribution 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, consideration of spatial and temporal correlation, over-dispersion

Graphical representation of predictions.

See full page

The aim of this course is to provide the statistical foundations needed to follow all the more advanced modules in the curriculum, so it's a general refresher. Descriptive statistics are reviewed (quantile, cumulative frequency polygon, sample estimators), simple tests are introduced, essential graphs for univariate and multivariate data are presented, the general principle of a statistical test, hypothesis design, 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.

See full page

The individual M1 internship lasts around three months, and must be carried out in a research laboratory or a non-academic structure, depending on the course concerned. It enables students to gain 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 to fit in with 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 presentation of the internship project. The internship work is assessed at a public presentation before a jury, during which the content of the dissertation and the quality of the answers to the jury's questions are evaluated. The student's behavior and dynamism during the internship are assessed by the internship supervisor.

See full page

The aim of this course is to understand the adaptive biology of organisms by considering individual and population responses to environmental variations. Concrete examples of 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 will show how physiological mechanisms are involved in ecology, from phenotypic and cognitive processes at the intra-individual level to functional variants between individuals and between species. Intraspecific variability, phenotypic plasticity and transgenerational effects will also be addressed. This course 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. target gene/protein), several experimental set-ups and various scales of organization of living organisms will be considered (molecule, gene, phenotype, individual, population, species).

See full page

See full page

This module provides an introduction to ethnobotany and ethnoecology, with a view to understanding the material and immaterial dimensions of the relationships between humans and their environment, with a particular focus on the plant world. We will be looking in particular at local systems of nomenclature and classification, perceptions and representations of nature, resource management uses and practices, and biocultural, ecological and evolutionary interactions. Ethnobotany and ethnoecology are disciplines at the interface of anthropology, botany and ecology, which can 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.

See full page

"The aim of this course is to complement the first semester's teaching by developing the issues involved in the evolution of phenotypes and the main associated methodological approaches. Lessons 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-theoretic formalization, adaptive dynamics, quantitative genetic approaches and the work of confronting theoretical predictions with empirical data. Teaching includes:

1) lectures on the main concepts of evolutionary ecology;

2) tutorials focusing on document studies and exercises".

See full page

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

Synthetic content of the EU:

- Independent tutored work: identification of a relevant scientific question; bibliographical synthesis 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.

Type of subject:

The topics can be based on any question identified by the students (in groups of 3/4), and validated by the teaching team, and draw on different approaches to suit the expectations of the different courses. For example, students may propose a field or experimental sampling 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 the students in the materials and methods requested in M1S2, with a provisional timetable for the project's progress and identification of the tasks that each student will carry out within each group as part of the project's implementation in M2S3. Projects must also be financially realistic, with a provisional budget, and must be able to be finalized within the time available in M2S3.

Assessment of knowledge:

Teaching is based on a problem-based learning approach, and students are assessed on how they progress in constructing their approach (40% of CC), as well as on their ability to present and defend their project at a final oral (60% of the overall mark)."

See full page