The course starts with a revision of multiple linear regression, followed by a basic introduction to generalised additive models (GAM) to analyse continuous data, count data and binary/proportional data.

In the second part of the course generalised additive mixed effects models (GAMM) are introduced to analyse nested data.

During the course several case studies are presented, in which the statistical theory is integrated with applied analyses in a clear and understandable manner.

We begin with an introduction to R and provide a protocol for data exploration to avoid common statistical problems. We will discuss how to detect outliers, deal with collinearity and transformations.

Por Ian Baldwin (Director of the Department of Molecular Ecology, Max Planck Institute for Chemical Ecology).

Por Anna Sapfo (Department of Computational Biology, University of Lausanne, Switzerland and Swiss Institute of Bioinformatics, Lausanne, Switzerland).

Por Scott R. Miller (Professor at University of Montana).

Por Sara Magalhães (Assistant Professor, Evolutionary Ecology Group - cE3c).

With this course, we aim at providing the participants with the basics of lichen biology and ecology, biomonitoring and data analysis methods to allow the use of lichens for the interpretation of the environmental conditions and the development of a responsible scientific-based environmental management.

Currently, climate changes or alterations are known to be reflected on the stable isotope ratios of Hydrogen, Nitrogen, Carbon, Oxygen and Sulphur present in atmospheric gas forms, fresh or ocean water, as well as in plants and animals and organic matter in the soil. Samples from those matrices can provide a record for such changes across a given length of time and / or space. Also, ecological and physiological processes often reflect on stable isotope ratios, again setting a record in plant, animal or other living tissues.