This unit covers the following concepts and tools : principles and sources of ecological cartography; georeferencing; GIS and map algebra; telemetry and on-board measuring equipment; spatial interpolation; database management. These tools are used in a sampling or experimental plan.
Theoretical learning outcomes:
• Knowledge of ecological mapping, georeferencing and telemetry methods.
• Acquiring knowledge about analysis of spatial distributions and spatial modelling (objectives, principles, field of application, implementation, interpretation of the results).
• Acquiring knowledge in database systems and to be able to use such systems.
• Acquiring concepts of metrology in the ecological field.
Technical learning outcomes:
• Building a Geographic Information System (QuantumGIS and interface with other GIS) using public databases, satellite data, and georeferenced data from field sessions.
• Using this GIS in order to plan a sampling field session.
• Applying spatial methods of data analysis (Quantum GIS and R software) and correctly interpret the results.
• Writing a concise and precise report concerning the collection and analysis of spatial ecological data.
• Assessing metrological quality of environmental data collected.
Knowledge of basic statistics, descriptive statistics, General Linear Models (GLM), anova, χ2, and non parametric statistics.
Lectures, seminars, practicals
Reports on the content of the sessions, oral and written exams.
- Bivand, R.S., Pebesma, E.J., Gomez-Rubio, V., 2013. Applied spatial data analysis with R. Second edition. Springer, New York et web tutoriels (QGIS, etc.).
- Crawley, M.J. 2007. The R book. John Wiley & Sons, Ltd. 942 pp.
- Dalgaard, P. (2002) Introductory statistics with R. Springer 267pp.
- Grafen, A. and Hails, R. 2002. Modern statistics for the life sciences. Oxford University Press, Oxford. 351pp.
- Legendre, P. and Legendre, L. 2012. Numerical Ecology. Elsevier, Amsterdam.
- Pinheiro, J.C. and Bates, D.M. 2000. Mixed effects models in S and Splus. Springer, New York:528 pp.
- Siegel, S. and Castellan, N. J. J. 1988. Non parametric statistics for the behavioral sciences. McGraw-Hill International Editions, New York. 399pp.
- Venables, W. N. and Ripley, B. D. 2002. Modern applied statistics with S. Springer, New York: 501 pp.
- Wood, S. (2006) Generalized Additive Models: An Introduction with R. Chapman & Hall.
- Zuur, A., Ieno, EN., Walker, N., Saveliev, AA., and Smith, GM. 2009. Mixed Effects Models and Extensions in Ecology with R. Springer.
Patrick GIRAUDOUX, firstname.lastname@example.org