Revolution V: quantitative ecology and spatial prediction of species distribution

Summary

Ecological research is becoming increasingly
quantitative, yet students often opt out of courses in mathematics and
statistics, unwittingly limiting their ability to carry out research in the
future. This course provides a practical introduction to quantitative ecology
for students and practitioners who have realised that they need this
opportunity. The course’s practical value is enhanced by extensive use of
biological examples and the computer language R for graphics, programming and
data analysis.

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Sessions

aRound
Description: installation and management of R packages. Review of packages. Input and output of data.

useR
Description: R session. Elements of the language.

gRaphics
Description: plotting functions and parameters.

autoR
Description: basic R programming and automatize tasks.

wRite
Description: preparing statistical reports using R.

Rspatial
Description: analysis of vector and raster cartography, also connecting with GRASS and QGIS.

aRtistics
Description: experimental design. Hypothesis contrast, ANOVA. Basic multi-variate statistics.

multivaR
Description: diversity and multivariate analysis: ordination and gradient analyses, ENFA (Ecological Niche Factor Analysis), habitat suitability maps, metapopulation simulations.

lineaR
Description: construction, optimization and evaluation of linear models. Representation and spatial interpretation.

modelaRt
Description: construction, optimization and evaluation of non-linear models. Representation and spatial interpretation.

geneRate
Description: importation of genetic data, basic diversity estimations, genetic distances, boundaries detection, polyploidy, spatial autocorrelation, Bayesian clustering. Representation and spatial interpretation.

Prerequisites

This course requires some prior experience in statistics
and elemental mathematics. Knowing object-oriented programming is not needed.

We will provide students with a selection of data sets
with which to work, however participants are encouraged to bring their own
data.

ECTS Credits

Course corresponds to ECTS credits.

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Grants

We offer 4 grants for students. The grant will cover the half of the expenses for the course.
If you are interested, you should submit a short CV, a justification of your situation and a letter of motivation, explaining why and how do you think this
course will improve you and your professional development, and how the grant will help you.
The decision won't be subjected to appeal.