Community analysis in R
Common statistical techniques used in community ecology.
This course explores the statistical methods commonly used in community ecology using the R programming language. There is an important theoretical component since the basis of multivariate methods are introduced and analized carefully. It is organized by Cousteau Consultant Group and taught in six days, three hours per day. In this page you can find a brief summary of the topics and R codes discussed during this course. Paola Galloso is an important contributor to the material presented in this course. Information presented here only available in Spanish. I hope to translate this material to English soon.
Course programme
The following topics are discussed:
- Day 1: Concepts in community ecology. Data exploration. Diversity indices.
- Day 2: Diversity types. Rarefaction. Species-abundance plots. Data transformation.
- Day 3: Distance measures. Cluster analysis. Species indicators.
- Day 4: Eigenvalues and eigenvectors. Unconstrained ordination: PCA.
- Day 5: Unconstrained ordination: CA and NMDS.
- Day 6: Canonical ordination: RDA and CCA. Beta diversity.
Objectives
- Introduce concepts in community ecology
- Introduce statistical methods used in community analysis
- Familiarize with R libraries used in community analysis
Prerequisite
- Basic statistic concepts
- Basic programming in the R language
