Duration
Introduction to marine ecosystems modelling : 15h Th, 15h Pr
Mathematical analysis and modelling methods applied to the environment : 20h Th, 20h Pr
Number of credits
| Master in oceanography (120 ECTS) (Erasmus Mundus ECT+ : Environmental Contamination and Toxicology) | 6 crédits |
Lecturer
Introduction to marine ecosystems modelling : Marilaure Grégoire
Mathematical analysis and modelling methods applied to the environment : Marilaure Grégoire
Coordinator
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Introduction to the basics of environmental modelling with exercises in R.
Part Mathematical analysis:
The course will involve the following chapters:
1) Concepts and tools of mathematical analysis: revision of basic mathematics: function, limit and asymtotic behavior, derivative function (simple, composite and material, Taylor expansion), primitive and integration, basics of modelling (mass balance equation), (moving) averaging of continuous function, ..Remediation exercises will be organized.
2) Dimensional analysis: dimensions, principle of dimensional homogeneity, characteristic length and time scales. Dimensional analysis, Pi theorem, systematic determination of dimensionless products, ..
3) Interpolation: unidimensional and multi-dimensional interpolation, linear estimation, objective analysis,
4) Analysis of time series: generalities, Fourier series and transform, filtering,
5) Dynamical modelling with one equation: the Malthusian growth model, Verhulst logistic model, equilibrium and stability, linear perturbation analysis, solution of basic ordinary differential equations,
6) Dynamic modelling with interactions: modelling of biochemical transformation, composed reactions, prey-predator, species competition, search for steady state solution, space phase analysis, and analyze the stability (linear perturbation, determination of the Jacobian matrix). R exercises will be organized.
7) Modelling with partial differential equations: continuity equations, advection-diffusion equation in 3D and 1D , spectral window, ..
Part marine modeling:
CHAPTER 1 Introduction
- What is a model?
- Why do we need models?
- Conceptual model
- Mathematical model formulation
- Formulation of ecological interactions
- Chemical reactions
- Inhibition
- Coupled model equations
- Impact of physical conditions
- Taonomy of spatial models
- Spatial boundary conditions
- Example: competitive interactions in a lattice model
- In situ measurement
- Literature-Derived parameters
- Calib_ters.43
- Initial conditions
- Analytical solutions of differential equations
- Numerical solution of differential equations
- Steady-state and stability analysis
- Dimensional homogeneity and consistency of units
- Conservation of energy and mass
- Testing the correctness of the model solution
- Testing the internal logic of the model
- Model verification
- Model validity
- Model sensitivity
- Example_74
- Example of the conservation principle: a mass budget of a marine bay
- Strategic versus tactic models
- Continuous and discrete time models
- Deterministic and stochastic models
- Density-biomass specific models
- Physiological - individual-based - population - ecosystem models
- Example: growth of a Daphnia individual
- Taxonomy of differential equations
- Solving difference equations
Introduction to marine ecosystems modelling
Introduction to the basics of environmental modelling with exercices in R.
Part Mathematical analysis:
The course will involve the follwoing chapters:
1) Concepts and tools of mathematical analysis: revision of basic mathematics: function, limit and asymtotic behavior, derivative function (simple, composite and material, taylor expansion), primitive and integration, basics of modelling (mass balance equation), (moving) averaging of continuous function, ..Remediation exercices will be organized.
2) Dimensional analysis: dimensions, principle of dimensional homogeneity, characteristic length and time scales. Dimensionnal analysis, Pi theorem, systematic determination of dimensionless products, ..
3) Interpolation: unidimensional and multi-dimensional interpolation, linear estimation, objective analysis,
4) Analysis of time series: generalities, Fourier series and transform, filtering,
5) Dynamical modelling with one equation: the malthusian growth model, Verhulst logistic model, equilibrium and stability, linear perturbation analysis, solution of basic ordinary differential equations,
6) Dynamic modelling with interactions: modelling of biochemical transformation, composed reactions, prey-preadtor, species competition, serach for steatdy state solution, space phase analysis, and analyse the stability (linear pertrubation, determination of the Jacobian matrix). R exercices will be organized.
7) Modelling with partial differential equations: continuity equations, adevctionn-diffusion eqaution in 3D and 1D , spectral window, ..
Part marine modellin:
CHAPTER 1 Introduction
- What is a model?
- Why do we need models?
- Conceptual model
- Mathematical model formulation
- Formulation of ecological interactions
- Chemical reactions
- Inhibition
- Coupled model equations
- Impact of physical conditions
- Taonomy of spatial models
- Spatial boundary conditions
- Example: competitive interactions in a lattice model
- In situ measurement
- Literature-Derived parameters
- Calib_ters.43
- Initial conditions
- Analytical solutions of differential equations
- Numerical solution of differential equations
- Steady-state and stability analysis
- Dimensional homogeneity and consistency of units
- Conservation of energy and mass
- Testing the correctness of the model solution
- Testing the internal logic of the model
- Model verification
- Model validity
- Model sensitivity
- Example_74
- Example of the conservation principle: a mass budget of a marine bay
- Strategic versus tactic models
- Continuous and discrete time models
- Deterministic and stochastic models
- Density-biomass specific models
- Physiological - individual-based - population - ecosystem models
- Example: growth of a Daphnia individual
- Taxonomy of differential equations
- Solving difference equations
Mathematical analysis and modelling methods applied to the environment
Introduction to the basics of environmental modelling with exercices in R.
Part Mathematical analysis:
The course will involve the follwoing chapters:
1) Concepts and tools of mathematical analysis: revision of basic mathematics: function, limit and asymtotic behavior, derivative function (simple, composite and material, taylor expansion), primitive and integration, basics of modelling (mass balance equation), (moving) averaging of continuous function, ..Remediation exercices will be organized.
2) Dimensional analysis: dimensions, principle of dimensional homogeneity, characteristic length and time scales. Dimensionnal analysis, Pi theorem, systematic determination of dimensionless products, ..
3) Interpolation: unidimensional and multi-dimensional interpolation, linear estimation, objective analysis,
4) Analysis of time series: generalities, Fourier series and transform, filtering,
5) Dynamical modelling with one equation: the malthusian growth model, Verhulst logistic model, equilibrium and stability, linear perturbation analysis, solution of basic ordinary differential equations,
6) Dynamic modelling with interactions: modelling of biochemical transformation, composed reactions, prey-preadtor, species competition, serach for steatdy state solution, space phase analysis, and analyse the stability (linear pertrubation, determination of the Jacobian matrix). R exercices will be organized.
7) Modelling with partial differential equations: continuity equations, adevctionn-diffusion eqaution in 3D and 1D , spectral window, ..
Learning outcomes of the learning unit
To teach the students the basics of mathematical modeling with practical applications.
Introduction to marine ecosystems modelling
To teach the students the basics of mathematical modeling with practical applications.
Mathematical analysis and modelling methods applied to the environment
To teach the students the basics of mathematical modeling with practical applications.
Prerequisite knowledge and skills
Basic mathematics
Introduction to marine ecosystems modelling
Basic mathematics
Mathematical analysis and modelling methods applied to the environment
Basic mathematics
Planned learning activities and teaching methods
Mode of delivery (face to face, distance learning, hybrid learning)
Face to face lecture and exercices. The student will have to prepare exercies at home that will be corrected during the next lecture.
Introduction to marine ecosystems modelling
Face to face lecture and exercices. The student will have to prepare exercies at home that will be corrected during the next lecture.
Mathematical analysis and modelling methods applied to the environment
Face to face lecture and exercices. The student will have to prepare exercies at home that will be corrected during the next lecture.
Organisational adjustments related to the current health context
Recommended or required readings
Lecture notes will be maed available as well as practical exercices in R (Rmd files).
Introduction to marine ecosystems modelling
Lecture notes will be maed available as well as practical exercices in R (Rmd files).
Mathematical analysis and modelling methods applied to the environment
Lecture notes will be maed available as well as practical exercices in R (Rmd files).
Assessment methods and criteria
Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.
Examination:
A homework will be required and is due for January 15th.
For those who failed in January, another exam will be planned in August/September.
Introduction to marine ecosystems modelling
Examination:
A homework will be required and is due for January 15th.
For those who failed in January, another exam will be planned in August/September.
Mathematical analysis and modelling methods applied to the environment
An online written test via eCampus in january (first session).
A written test in August/September (retake).
Work placement(s)
Not foreseen
Introduction to marine ecosystems modelling
Not foreseen
Mathematical analysis and modelling methods applied to the environment
Not foreseen
Organizational remarks
None
Introduction to marine ecosystems modelling
None
Mathematical analysis and modelling methods applied to the environment
None
Contacts
Marilaure Grégoire
MAST research group
Department of Astrophysics, Geophysics and Oceanography (AGO)
Introduction to marine ecosystems modelling
Marilaure Grégoire
MAST research group
Department of Astrophysics, Geophysics and Oceanography (AGO)
Mathematical analysis and modelling methods applied to the environment
Marilaure Grégoire
MAST research group
Department of Astrophysics, Geophysics and Oceanography (AGO)